Checking for stationary in time series
Dear all,
1) Please fit appropriate models for the three data step by step.
2) You may also use the auto.arima() function in R and it returns a best ARIMA model according to either AIC, AICc or BIC value. The function conducts a search over possible models within the order constraints provided. For example,
auto.arima(y, d=NA, D=NA, max.p=5, max.q=5,)
max.p: Maximum value of p; max.q Maximum value of q.
3) Alternatively if you want to choose the model yourself, use the arima() function in R (refer to R for ARIMA pdf).
4) Use diff () function to make data stationary.
5) The data LakeHuron used in R for ARIMA pdf can be found in R.
The assignment is due on next Friday, 27 March . Please submit a report online including R code and output.
In addition, you may use the following R command
adf.test()
to test whether the data are stationary. The attached pdf document contains more
1) Please fit appropriate models for the three data step by step.
2) You may also use the auto.arima() function in R and it returns a best ARIMA model according to either AIC, AICc or BIC value. The function conducts a search over possible models within the order constraints provided. For example,
auto.arima(y, d=NA, D=NA, max.p=5, max.q=5,)
max.p: Maximum value of p; max.q Maximum value of q.
3) Alternatively if you want to choose the model yourself, use the arima() function in R (refer to R for ARIMA pdf).
4) Use diff () function to make data stationary.
5) The data LakeHuron used in R for ARIMA pdf can be found in R.
The assignment is due on next Friday, 27 March . Please submit a report online including R code and output.
In addition, you may use the following R command
adf.test()
to test whether the data are stationary. The attached pdf document contains more
